Abstract
The authors reveal some fundamental problems with inverse
filtering: inaccuracies in finding the frequency-domain representation,
windowing effects, and border effects. A general, matrix-based method
using regularization that eliminates these problems is presented. The
method is confirmed experimentally, with the results showing an RMS
(root mean square) error of 1.3%
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